Legal claims defining the scope of protection. Each claim is shown in both the original legal language and a plain English translation.
1. A method for determining a predictive indicator based on network performance at regular intervals for each of a plurality of subscribers, the method comprising: providing a radio access network (RAN) associated with a service provider network, the RAN including a plurality of base stations, in which each base station has a coverage area; enabling a plurality of mobile devices to be communicatively coupled to the RAN; communicatively coupling a network load traffic management compononent to the RAN, wherein the network load traffic management component includes a subscriber scoring module and a subscriber scoring database that operates on a server processor and a server memory; identifying, with the network load traffic management component, at least one network event corresponding to a RAN control plane; monitoring, with the network load traffic management component, each network event for a session time wherein each session time is associated with each subscriber interacting with the RAN; repeatedly, determining a performance measurement for each network event associated with each session time; recording, with the network load traffic management component, the performance measurement for each network event over a timeline, wherein each performance measurement is associated with each of the plurality of session times for each subscriber; generating, with the network load traffic management component, a subscriber score based on the plurality of performance measurements for each network event; and generating, with the network load traffic management component, a predictive indicator score based on a plurality of subscriber scores and a plurality of behavioral analytics associated with each subscriber.
2. The method of claim 1 wherein the behavioral analytics includes a mobility attribute.
This invention relates to behavioral analytics systems, specifically those that analyze user behavior to detect anomalies or security threats. The core technology involves monitoring and processing behavioral data to identify patterns indicative of suspicious or unauthorized activity. A key aspect of this system is the inclusion of a mobility attribute within the behavioral analytics. The mobility attribute tracks and evaluates changes in user location, movement patterns, or device mobility to enhance threat detection. For example, sudden or unusual movements, such as rapid relocations or access from unexpected locations, may trigger alerts. The system may also integrate additional behavioral metrics, such as user activity frequency, access times, or interaction patterns, to refine detection accuracy. By incorporating mobility data, the system improves its ability to distinguish between legitimate and malicious behavior, reducing false positives and enhancing security. This approach is particularly useful in environments where user mobility is a factor, such as enterprise networks, IoT devices, or remote access systems. The invention aims to provide a more comprehensive and adaptive security solution by leveraging mobility as a critical behavioral indicator.
3. The method of claim 2 wherein the mobility attribute includes at least one of a location for each mobile device, an activity level for each mobile device, at least one used service associated with each mobile device, at least one tariff associated with each mobile device and a revenue associated with each mobile device.
This invention relates to mobile device management in wireless communication networks, specifically addressing the need to optimize network resource allocation and service delivery based on dynamic mobility attributes of mobile devices. The method involves tracking and analyzing mobility attributes to enhance network performance, user experience, and revenue management. The mobility attributes include location data for each mobile device, activity levels indicating usage patterns, services actively used by each device, applicable tariffs or pricing plans, and revenue generated from each device. By collecting and processing these attributes, the system can dynamically adjust network resources, prioritize services, and optimize tariff structures. For example, location data may be used to predict device movement and pre-allocate network resources, while activity levels help identify high-usage periods for load balancing. Service and tariff data enable personalized service delivery and pricing adjustments, while revenue tracking supports financial optimization. The method ensures efficient resource utilization, improved service quality, and tailored user experiences by leveraging real-time mobility insights. This approach benefits both network operators and users by reducing congestion, enhancing service reliability, and aligning pricing with actual usage patterns. The system dynamically adapts to changing conditions, ensuring optimal performance across diverse network environments.
4. The method of claim 1 wherein the predictive indicator score is associated with a net promoter score.
A system and method for predicting customer satisfaction in a telecommunications network. The invention addresses the problem of proactively identifying customers likely to have a negative experience or churn. A predictive indicator score is generated, which is a quantitative measure of a customer's predicted satisfaction level. This predictive indicator score is specifically associated with or mapped to a Net Promoter Score (NPS). The association allows for interpretation of the predictive indicator score in the context of a well-established customer loyalty metric. This enables service providers to understand the degree of potential customer dissatisfaction represented by the predictive indicator score by correlating it with NPS categories such as Promoters, Passives, and Detractors. By linking the predictive indicator score to NPS, the system facilitates targeted interventions and proactive customer service strategies to improve customer retention and overall satisfaction.
5. The method of claim 1 wherein the session time includes a call duration.
A system and method for managing communication sessions, particularly in telecommunication or networked environments, addresses the challenge of accurately tracking and analyzing session interactions. The invention involves monitoring and recording session time, including call duration, to provide detailed insights into communication patterns. The method captures the start and end times of a session, calculates the total duration, and integrates this data into a broader analysis framework. This allows for improved performance monitoring, billing accuracy, and user behavior analysis. The system may also correlate session time with other metrics, such as network conditions or user activity, to enhance decision-making. By focusing on call duration as a key parameter, the invention enables more precise tracking of communication sessions, supporting applications in customer service, network optimization, and compliance reporting. The method ensures reliable timekeeping and data integrity, making it suitable for real-time and post-session analysis.
6. The method of claim 1 wherein the predictive indicator score for each subscriber is used to evaluate a network performance of the radio access network.
This invention relates to evaluating network performance in a radio access network (RAN) by analyzing predictive indicator scores for individual subscribers. The method involves generating a predictive indicator score for each subscriber based on their usage patterns, device capabilities, and network conditions. These scores are then used to assess the overall performance of the RAN, identifying areas where improvements may be needed. The predictive indicator score may incorporate factors such as data throughput, latency, signal strength, and historical performance metrics. By analyzing these scores across multiple subscribers, the system can detect trends, predict potential network issues, and optimize resource allocation. The method may also involve comparing the predictive indicator scores against predefined thresholds to trigger automated adjustments or alerts for network operators. This approach enables proactive management of network performance, ensuring a more reliable and efficient RAN for all users. The invention is particularly useful in dynamic environments where network conditions and subscriber demands vary frequently.
7. The method of claim 1 wherein the network event includes at least one of a registration, a SIP message, a plurality of media traffic and a plurality of bearer traffic.
This invention relates to network monitoring and analysis, specifically for detecting and processing network events in communication systems. The problem addressed is the need to efficiently identify and analyze various types of network events to improve system performance, security, and reliability. The method involves monitoring a communication network to detect network events, which may include registrations, SIP (Session Initiation Protocol) messages, media traffic, and bearer traffic. These events are captured and processed to extract relevant data, such as timestamps, source/destination identifiers, and payload information. The extracted data is then analyzed to detect anomalies, performance issues, or security threats. The analysis may involve pattern recognition, statistical analysis, or machine learning techniques to identify deviations from normal behavior. The method also includes generating alerts or reports based on the analysis results, which can be used for troubleshooting, optimization, or security enforcement. The system may integrate with existing network management tools to provide real-time insights and automated responses to detected events. By comprehensively monitoring and analyzing these diverse network events, the invention aims to enhance network visibility, reduce downtime, and improve overall system efficiency.
8. The method of claim 1 wherein the performance measurement includes a quality of service.
A system and method for monitoring and evaluating the performance of a network or computing system, particularly focusing on quality of service (QoS) metrics. The invention addresses the need for accurate and real-time assessment of system performance to ensure optimal operation and user experience. The method involves collecting performance data from various components of the system, such as network latency, bandwidth utilization, packet loss, and error rates. This data is then analyzed to generate performance measurements, including QoS metrics, which quantify the system's ability to meet predefined service standards. The QoS metrics may include parameters like throughput, delay, jitter, and reliability, which are critical for applications requiring consistent and high-quality service, such as video streaming, voice over IP, or real-time data processing. The system may also compare the measured performance against benchmark values or service-level agreements to identify deviations and trigger corrective actions. Additionally, the method may involve logging performance data over time to detect trends, predict potential failures, and optimize system configurations. The invention is applicable in various domains, including telecommunications, cloud computing, and enterprise IT infrastructure, where maintaining high performance and reliability is essential.
9. A system for determining a predictive indicator based on network performance at regular intervals for each of a plurality of subscribers, the system comprising: a radio access network (RAN) associated with a service provider network, the RAN including a plurality of base stations, in which each base station has a coverage area; a plurality of mobile devices to be communicatively coupled to the RAN; a network load traffic management component communicatively coupled to the RAN, wherein the network load traffic management component includes a subscriber scoring module and a subscriber scoring database that operates on a server processor and a server memory; the network load traffic management component identifies at least one network event; the network load traffic management component monitors each network event for a session time, in which each session time is associated with each subscriber interacting with the RAN; the network load traffic management component repeatedly determines a performance measurement for each network event associated with each session time; the network load traffic management component records the performance measurement for each network event over a timeline, wherein each performance measurement is associated with each of the plurality of session times for each subscriber; the network load traffic management component generating a subscriber score based on the plurality of performance measurements for each network event; and the network load traffic management component generating a predictive indicator score based on a plurality of subscriber scores and a plurality of behavioral analytics associated with each subscriber.
The system monitors network performance for multiple subscribers in a radio access network (RAN) to generate predictive indicators. The RAN includes base stations with coverage areas, and mobile devices connect to the network. A network load traffic management component, running on a server with a processor and memory, tracks network events and their performance over time. For each subscriber, the system records performance measurements during network events, such as session times, and stores these in a subscriber scoring database. The system calculates a subscriber score based on these performance measurements and generates a predictive indicator score by analyzing subscriber scores alongside behavioral analytics. This helps assess subscriber behavior and network performance trends, enabling proactive management of network resources. The system continuously monitors and evaluates performance to improve service quality and predict future network conditions.
10. The system of claim 9 wherein the behavioral analytics include a mobility attribute, wherein the mobility attribute further includes at least one of a location for each mobile device, an activity level for each mobile device, at least one used service associated with each mobile device, at least one tariff associated with each mobile device and a revenue associated with each mobile device.
This invention relates to a system for analyzing mobile device behavior in a network environment. The system addresses the challenge of efficiently monitoring and assessing mobile device usage patterns to optimize network performance and service delivery. The system collects and processes behavioral analytics data from mobile devices, including mobility attributes such as location, activity level, used services, associated tariffs, and revenue generated by each device. These attributes help identify usage trends, service demand, and revenue opportunities. The system may also track device interactions with network services, allowing for dynamic adjustments to improve service quality and resource allocation. By integrating these analytics, the system enables network operators to enhance user experience, optimize service offerings, and maximize revenue potential. The mobility attributes provide a comprehensive view of device behavior, supporting data-driven decision-making for network management and service provisioning.
11. The system of claim 9 wherein the predictive indicator score is associated with a net promoter score.
A system for evaluating customer satisfaction and loyalty in a service or product environment generates a predictive indicator score that quantifies the likelihood of a customer recommending the service or product to others. This predictive indicator score is specifically linked to a net promoter score (NPS), a widely used metric in customer experience management that measures customer willingness to promote a brand. The system collects data from customer interactions, such as surveys, feedback, or usage patterns, and processes this data to derive the predictive indicator score. The score is then correlated with the net promoter score to provide actionable insights into customer sentiment and potential business growth. By associating the predictive indicator score with the net promoter score, the system enables businesses to identify high-value customers, predict churn risk, and optimize customer engagement strategies. The system may also include additional features, such as real-time monitoring of customer feedback and automated alerts for low satisfaction scores, to enhance decision-making and improve customer retention efforts. This approach helps organizations proactively address customer concerns and foster long-term loyalty.
12. The system of claim 9 wherein the session time includes a call duration.
A system for managing communication sessions, particularly in telecommunication or networked environments, addresses the challenge of efficiently tracking and analyzing session interactions. The system monitors and records session time, including call duration, to provide insights into communication patterns, resource utilization, and user behavior. By capturing detailed timing data, the system enables optimization of network performance, billing accuracy, and service quality. The session time tracking may involve real-time monitoring or post-session analysis, depending on the application. The system can integrate with existing telecommunication infrastructure, such as switches, routers, or cloud-based platforms, to collect and process session data. Additional features may include data storage, reporting, and analytics to derive actionable insights from the recorded session times. This system is particularly useful in industries requiring precise call duration tracking, such as telecommunications, customer service, and enterprise communication management. The inclusion of call duration as part of the session time ensures accurate billing, compliance with regulatory requirements, and improved service delivery. The system may also support automated alerts or notifications based on predefined thresholds or anomalies in session time data.
13. The system of claim 9 wherein the predictive indicator score for each subscriber is used to evaluate a network performance of the radio access network.
This invention relates to evaluating network performance in a radio access network (RAN) by analyzing predictive indicator scores for individual subscribers. The system monitors subscriber behavior and network conditions to generate predictive scores that reflect the likelihood of future performance issues, such as congestion, latency, or service degradation. These scores are derived from real-time data, including signal strength, data usage patterns, and network load, and are used to assess overall RAN performance. The system may also correlate these scores with specific network events or subscriber actions to identify trends or potential failures. By continuously evaluating predictive scores, the system enables proactive network optimization, reducing downtime and improving service quality. The invention may integrate with existing network management tools to provide actionable insights for network operators. The predictive scoring mechanism helps distinguish between temporary fluctuations and persistent performance issues, allowing for targeted interventions. This approach enhances network reliability and user experience by anticipating and mitigating potential problems before they impact subscribers.
14. The system of claim 9 wherein the network event includes at least one of a registration, a SIP message, a plurality of media traffic and a plurality of bearer traffic.
This invention relates to a network monitoring system designed to analyze and process various types of network events in real-time. The system is particularly useful in telecommunications networks, where it monitors and processes events such as device registrations, SIP (Session Initiation Protocol) messages, media traffic, and bearer traffic. These events are captured and analyzed to detect anomalies, optimize performance, or enforce security policies. The system includes a network event processor that receives and processes these events. The processor is configured to handle different types of network traffic, including signaling messages (like SIP) and media/bearer traffic, which are essential for voice and data communications. The system may also include a data storage component to log and store event data for further analysis or compliance purposes. Additionally, the system may incorporate machine learning or pattern recognition techniques to identify trends, predict failures, or detect malicious activities. The processed data can be used to generate alerts, adjust network configurations, or trigger automated responses. The system is scalable and can be deployed in various network environments, including 4G, 5G, or IP-based networks, to ensure efficient and secure communication services.
15. The system of claim 9 wherein the performance measurement includes a quality of service.
A system for monitoring and evaluating the performance of a network or computing infrastructure includes a performance measurement module that assesses various operational metrics. The system specifically measures quality of service (QoS) parameters, such as latency, throughput, packet loss, and reliability, to determine the efficiency and effectiveness of the network or system. The performance measurement module collects real-time data from network devices, applications, or other components and analyzes this data to generate insights into system performance. These insights are used to identify bottlenecks, optimize resource allocation, and ensure that service-level agreements (SLAs) are met. The system may also include a reporting module that presents the performance data in a user-friendly format, allowing administrators to make informed decisions. Additionally, the system may integrate with automated tools to trigger corrective actions when performance thresholds are violated. By continuously monitoring QoS metrics, the system ensures that the network or computing infrastructure operates at an optimal level, minimizing downtime and improving user experience.
16. A system for determining a predictive indicator based on network performance at regular intervals for each of a plurality of subscribers, the system comprising: a radio access network (RAN) associated with a service provider network, the RAN including a plurality of Base stations, in which each Base station has a coverage area; a plurality of mobile devices to be communicatively coupled to the RAN; a network load traffic management component communicatively coupled to the RAN, wherein the network load traffic management component includes a subscriber scoring module and a subscriber scoring database that operates on a server processor and a server memory; the network load traffic management component identifies at least one network event corresponding to a RAN control plane; the network load traffic management component monitors each network event for a session time, in which each session time is associated with each subscriber interacting with the RAN; the network load traffic management component repeatedly determines a performance measurement for each network event associated with each session time; the network load traffic management component records the performance measurement for each network event over a timeline, wherein each performance measurement is associated with each of the plurality of session times for each subscriber; the network load traffic management component generating a daily subscriber score based on the plurality of performance measurements for each network event, wherein the performance measurement includes a Quality of Service parameter; the network load traffic management component generating a predictive indicator score based on a plurality of daily subscriber scores and a plurality of behavioral analytics associated with each subscriber; and wherein the behavioral analytics include a mobility attribute, wherein the mobility attribute further includes at least one of a location for each mobile device, an activity level for each mobile device, at least one used service associated with each mobile device, at least one tariff associated with each mobile device and a revenue associated with each mobile device.
The system monitors network performance for multiple subscribers at regular intervals to generate predictive indicators. It operates within a radio access network (RAN) managed by a service provider, where base stations provide coverage to mobile devices. A network load traffic management component, including a subscriber scoring module and database, tracks network events related to the RAN control plane. For each subscriber session, the system measures performance metrics over time, recording these measurements to analyze trends. Daily subscriber scores are calculated based on quality of service parameters from these measurements. Additionally, the system generates a predictive indicator score by combining daily subscriber scores with behavioral analytics, such as device location, activity level, used services, tariffs, and revenue. This predictive scoring helps assess subscriber behavior and network performance, enabling better resource allocation and service optimization. The system dynamically evaluates network interactions to improve service quality and efficiency.
17. The system of claim 16 wherein the predictive indicator score is associated with a net promoter score.
A system for analyzing customer feedback data to generate predictive indicators of customer satisfaction and loyalty. The system processes feedback data from multiple sources, such as surveys, reviews, or social media, to extract sentiment and key topics. It then applies machine learning models to generate a predictive indicator score that quantifies the likelihood of a customer becoming a promoter or detractor. This predictive indicator score is specifically linked to a net promoter score (NPS), a widely used metric in customer experience management that measures customer willingness to recommend a product or service. The system may also include features for tracking changes in predictive scores over time, identifying trends, and providing actionable insights to improve customer satisfaction. The predictive indicator score helps businesses anticipate customer behavior and take proactive measures to enhance loyalty and reduce churn. The system may further integrate with existing customer relationship management (CRM) platforms to streamline data collection and analysis. By correlating predictive scores with NPS, the system enables more accurate forecasting of customer loyalty and business performance.
18. The system of claim 16 wherein the session time includes a call duration.
This invention relates to a system for managing and analyzing communication sessions, particularly focusing on tracking and utilizing session time metrics. The system addresses the need for accurate and detailed monitoring of communication interactions, such as calls, to improve efficiency, billing, and performance analysis. The system includes a session tracking module that records the duration of communication sessions, including call duration, to provide precise timing data. This module integrates with a data processing unit that analyzes the session time metrics to generate insights, such as usage patterns, performance metrics, and billing information. The system may also include a user interface for displaying the session time data in a user-friendly format, allowing administrators or users to review and interpret the information. Additionally, the system may incorporate a reporting module that generates detailed reports based on the session time data, which can be used for auditing, compliance, or optimization purposes. The system is designed to be scalable and adaptable, supporting various types of communication sessions beyond calls, such as video conferences or messaging sessions, while maintaining accurate time tracking. By providing comprehensive session time tracking and analysis, the system enhances the ability to monitor and optimize communication workflows, ensuring accurate billing and improving overall communication efficiency.
19. The system of claim 16 wherein the predictive indicator score for each subscriber is used to evaluate a network performance of the radio access network.
This invention relates to a system for evaluating network performance in a radio access network (RAN) by analyzing predictive indicator scores for subscribers. The system monitors subscriber behavior and network conditions to generate predictive scores that reflect the likelihood of future performance issues, such as congestion, latency, or service degradation. These scores are then used to assess overall network performance, enabling proactive optimization and troubleshooting. The system includes a data collection module that gathers real-time and historical data from network elements, such as base stations, switches, and subscriber devices. A predictive analytics engine processes this data to calculate individual subscriber scores based on factors like usage patterns, signal strength, and historical performance trends. The scores are dynamically updated to reflect changing conditions. A network performance evaluation module uses these predictive scores to analyze the RAN's efficiency, reliability, and capacity. By correlating subscriber scores with network metrics, the system identifies potential bottlenecks, predicts service disruptions, and recommends corrective actions. The system may also prioritize network resources for high-risk subscribers to maintain service quality. This approach improves network management by shifting from reactive to predictive maintenance, reducing downtime and enhancing user experience. The system is applicable to various RAN technologies, including 4G, 5G, and Wi-Fi networks.
20. The system of claim 16 wherein the network event includes at least one of a registration, a SIP message, a plurality of media traffic and a plurality of bearer traffic.
This invention relates to a network monitoring system designed to analyze and process various types of network events in real-time. The system is particularly useful in telecommunications and data networks where tracking and managing network activity is critical for performance optimization, security, and compliance. The system is configured to detect and process different types of network events, including device registrations, Session Initiation Protocol (SIP) messages, media traffic, and bearer traffic. These events are captured and analyzed to provide insights into network behavior, identify anomalies, and ensure efficient resource allocation. The system may also correlate these events to detect patterns, troubleshoot issues, or enforce policies. The network monitoring system is designed to handle high volumes of traffic and events, ensuring scalability and reliability. It may integrate with existing network infrastructure to provide a comprehensive view of network activity. The system can be deployed in various network environments, including IP-based networks, VoIP systems, and mobile networks, to enhance operational efficiency and security. By monitoring and analyzing these network events, the system helps operators maintain service quality, detect potential threats, and optimize network performance. The ability to process multiple types of traffic and messages ensures that the system is versatile and adaptable to different network scenarios.
Unknown
August 18, 2020
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